Turning dispersion into signal: density-split analyses of pairwise velocities

Abstract Pairwise velocities of the large-scale structure encode valuable information about the growth of structure. They can be observed indirectly through redshift-space distortions and the kinetic Sunyaev-Zeldovich effect. Whether it is Gaussian or non-Gaussian, the pairwise velocity has a broad distribution, but the cosmologically useful information lies primarily in the mean -the streaming velocities; the dispersion around the mean is often treated as a nuisance and marginalised over. This reduces the constraining power of our observations. We demonstrate that this is not necessarily the case, provided the underlying physics behind the dispersion is understood. By splitting the halo/galaxy samples according to their density environments and measuring the streaming velocities separately, the total signal-to-noise is several times greater than in conventional global measurements of the pairwise velocity distribution (PVD). This improvement arises because the global PVD is a composite of a series of near-Gaussian distributions with different means and dispersions, each determined by its local density environment. By splitting the data, we avoid cancellation between these opposing velocities, effectively turning the dispersion in the global PVD into a signal. Our findings indicate substantial potential for improving the analysis of PVD observations using the kinetic Sunyaev-Zeldovich effect and redshift-space distortions.

Authors

Institutions

Publication Details

Journal
Monthly Notices of the Royal Astronomical Society
Published
2026-05-09
DOI
https://doi.org/10.1093/mnras/stag881
Primary Topic
Galaxies: Formation, Evolution, Phenomena
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Turning dispersion into signal: density-split analyses of pairwise velocities

Yan-Chuan Cai, Aritra Kumar Gon
Monthly Notices of the Royal Astronomical Society
Galaxies: Formation, Evolution, Phenomena
article

Turning dispersion into signal: density-split analyses of pairwise velocities

Yan-Chuan Cai, Aritra Kumar Gon
article en

Abstract

Abstract Pairwise velocities of the large-scale structure encode valuable information about the growth of structure. They can be observed indirectly through redshift-space distortions and the kinetic Sunyaev-Zeldovich effect. Whether it is Gaussian or non-Gaussian, the pairwise velocity has a broad distribution, but the cosmologically useful information lies primarily in the mean -the streaming velocities; the dispersion around the mean is often treated as a nuisance and marginalised over. This reduces the constraining power of our observations. We demonstrate that this is not necessarily the case, provided the underlying physics behind the dispersion is understood. By splitting the halo/galaxy samples according to their density environments and measuring the streaming velocities separately, the total signal-to-noise is several times greater than in conventional global measurements of the pairwise velocity distribution (PVD). This improvement arises because the global PVD is a composite of a series of near-Gaussian distributions with different means and dispersions, each determined by its local density environment. By splitting the data, we avoid cancellation between these opposing velocities, effectively turning the dispersion in the global PVD into a signal. Our findings indicate substantial potential for improving the analysis of PVD observations using the kinetic Sunyaev-Zeldovich effect and redshift-space distortions.

Monthly Notices of the Royal Astronomical Society
Royal Observatory (GB), University of Edinburgh (GB)
Reduced inequalities
Openalex Percentile: Top 5%
Galaxies: Formation, Evolution, Phenomena
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.